Time series analysis and forecasting of chlamydia trachomatis incidence using surveillance data from 2008 to 2019 in Shenzhen, China.
Epidemiol Infect
; 148: e76, 2020 03 17.
Article
en En
| MEDLINE
| ID: mdl-32178748
ABSTRACT
Chlamydia trachomatis (CT) infection has been a major public health threat globally. Monitoring and prediction of CT epidemic status and trends are important for programme planning, allocating resources and assessing impact; however, such activities are limited in China. In this study, we aimed to apply a seasonal autoregressive integrated moving average (SARIMA) model to predict the incidence of CT infection in Shenzhen city, China. The monthly incidence of CT between January 2008 and June 2019 in Shenzhen was used to fit and validate the SARIMA model. A seasonal fluctuation and a slightly increasing pattern of a long-term trend were revealed in the time series of CT incidence. The monthly CT incidence ranged from 4.80/100 000 to 21.56/100 000. The mean absolute percentage error value of the optimal model was 8.08%. The SARIMA model could be applied to effectively predict the short-term CT incidence in Shenzhen and provide support for the development of interventions for disease control and prevention.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Infecciones por Chlamydia
/
Chlamydia trachomatis
Tipo de estudio:
Incidence_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
/
Screening_studies
Límite:
Humans
País/Región como asunto:
Asia
Idioma:
En
Revista:
Epidemiol Infect
Asunto de la revista:
DOENCAS TRANSMISSIVEIS
/
EPIDEMIOLOGIA
Año:
2020
Tipo del documento:
Article
País de afiliación:
China